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Compliance Automation Suite

$89

Automated compliance for GDPR, SOC 2, ISO 27001, and NIS2. Evidence collection scripts, DPIA templates, and audit preparation guide.

📁 37 files🏷 v2.0.0
PythonJSONMarkdownSQLShellAzureDatabricksPySparkSparkDelta Lake

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📁 File Structure 37 files

compliance-automation-suite/ ├── README.md ├── audits/ │ ├── __init__.py │ ├── catalog_inventory.py │ ├── compute_analysis.py │ ├── config.py │ ├── data_lineage.py │ ├── external_storage.py │ ├── job_inventory.py │ ├── query_history.py │ ├── secret_inventory.py │ ├── table_permissions.py │ ├── token_inventory.py │ └── utils.py ├── dashboards/ │ └── compliance_dashboard.sql ├── gdpr/ │ ├── consent_tracking.py │ ├── dpia_template.md │ ├── dsr_handler.py │ └── ropa_generator.py ├── mappings/ │ ├── gdpr_databricks_controls.md │ ├── iso27001_controls.md │ ├── nis2_checklist.md │ └── soc2_azure_controls.md ├── output/ │ └── .gitkeep ├── reports/ │ ├── __init__.py │ ├── html_report.py │ ├── json_report.py │ └── templates/ │ └── audit_report.html ├── run_audit.sh ├── scripts/ │ ├── access_control_audit.py │ ├── audit_log_validation.py │ ├── data_retention_check.py │ ├── encryption_verification.py │ └── network_security_check.py └── templates/ ├── audit_preparation.md ├── scheduling_guide.md └── soc2_evidence_binder.md

📖 Documentation Preview README excerpt

Compliance Automation Suite

Product ID: compliance-automation-suite

Version: 2.0.0

Price: $89 USD

Author: [Datanest Digital](https://datanest.dev)

Category: Enterprise

Overview

The Compliance Automation Suite provides production-ready tooling for organizations operating

on Databricks and Azure that must satisfy GDPR, SOC 2 Type II, ISO 27001, and the EU NIS2

Directive. Instead of manually assembling evidence and cross-referencing spreadsheets before

every audit cycle, this suite automates the heavy lifting: continuous control verification,

evidence collection, gap analysis, and audit-readiness reporting.

New in v2.0: The suite now includes a comprehensive operational audit module with 9

automated audit scripts covering catalog inventory, job analysis, secret management, compute

costs, storage security, token hygiene, query history, data lineage, and table permissions.

These operational audits use Python standard library only (no pip dependencies) and

produce HTML and JSON reports with findings mapped to compliance frameworks (GDPR, SOC 2,

ISO 27001, NIS2).

Every script is designed as a Databricks notebook or standalone Python module so it slots

directly into existing lakehouse architectures. The control mappings translate regulatory

language into concrete technical controls you can verify programmatically.

What's Included

Control Mappings (`mappings/`)

FileDescription
gdpr_databricks_controls.mdGDPR articles mapped to Databricks technical controls
soc2_azure_controls.mdSOC 2 Trust Service Criteria mapped to Azure services
iso27001_controls.mdISO 27001:2022 Annex A controls in spreadsheet format
nis2_checklist.mdNIS2 Directive (EU 2022/2555) compliance checklist

Compliance Audit Scripts (`scripts/`)

FileDescription
access_control_audit.pyAudit workspace ACLs, group memberships, token lifetimes
encryption_verification.pyVerify encryption at rest, in transit, and key management
data_retention_check.pyCheck data lifecycle against retention policies
audit_log_validation.pyValidate audit log completeness and integrity
network_security_check.pyAssess network security posture and segmentation

Operational Audit Module (`audits/`) — NEW in v2.0

A self-contained Python package with 9 automated audit scripts, a shared API client,

configuration module, and utility library. Zero pip dependencies — uses only Python

standard library (http.client, ssl, json, csv, logging, etc.).

FileDescription

... continues with setup instructions, usage examples, and more.

📄 Code Sample .py preview

audits/catalog_inventory.py #!/usr/bin/env python3 """ Catalog Inventory Audit ======================== Enumerates all Unity Catalog catalogs, schemas, and tables with metadata. Identifies orphaned schemas, empty catalogs, undocumented objects, and tables without owners -- all of which contribute to compliance drift. Why this matters for compliance: - GDPR Art. 30 requires a Record of Processing Activities (ROPA); a catalog inventory is the data-layer equivalent. - SOC 2 CC6.1 mandates asset classification; undocumented tables cannot be properly classified. - ISO 27001 A.8.1 requires an inventory of information assets. - NIS2 Art. 21 expects organisations to know what data they hold and where. """ from __future__ import annotations import sys import os from typing import Any, Dict, List # Allow standalone execution from within the audits/ directory if __name__ == "__main__": sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) from audits.config import UC_CATALOGS, UC_SCHEMAS, UC_TABLES from audits.utils import BaseAudit, Finding, save_json, url_encode class CatalogInventoryAudit(BaseAudit): """Inventory all Unity Catalog objects: catalogs, schemas, and tables. Produces a hierarchical snapshot of every data asset in the workspace, with metadata on ownership, documentation, and storage location. """ name = "catalog_inventory" description = "Lists all catalogs, schemas, and tables with metadata" def run(self) -> Dict[str, Any]: """Enumerate catalogs -> schemas -> tables from the Unity Catalog API.""" catalogs_raw = self.client.get(UC_CATALOGS) or {} catalogs = catalogs_raw.get("catalogs", []) self.logger.info("Found %d catalogs", len(catalogs)) catalog_list: List[Dict[str, Any]] = [] # ... 184 more lines ...
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